Solution Architect - Artificial Intelligence (9-10 yrs)

Role : Solution Architect AI.

Job Summary :

We are seeking an experienced Solution Architect specializing in AI with 9-10 years of experience to join our team.

The ideal candidate will possess a strong background in data and analytics, with a focus on AI technologies and solutions.

Years of Experience Required : 9-10 years.

Responsibilities :

- Collaborate with stakeholders across business and technical teams to understand needs and opportunities for AI integration.

- Design and architect secure, scalable, and cost-effective AI solutions, leveraging cutting-edge technologies like machine learning, deep learning, and natural language processing.

- Select and implement appropriate AI frameworks, tools, and libraries (e.g., TensorFlow, PyTorch, scikit learn) based on project requirements.

- Ensure solutions adhere to best practices in AI development, data security, and fairness considerations.

- Lead the development and implementation of proof-of-concept (POC) demonstrations for proposed solutions.

- Develop and maintain technical roadmaps for AI initiatives, aligning with long-term business goals.

- Work collaboratively with data scientists, engineers, and operations teams to bring AI solutions to life.

- Stay up-to-date on the latest advancements in AI research and development.

Tech Skills (Required) :

- 5+ years of experience in software architecture or a related technical role.

- In-depth knowledge of AI concepts, including machine learning, deep learning, and natural language processing.

- Strong understanding of software development lifecycle (SDLC) methodologies for AI projects.

- Experience with cloud platforms and containerization technologies (e.g., AWS, Azure, GCP, Docker) for deploying AI solutions.

- Proficiency in programming languages commonly used in AI development (e.g., Python, R).

- Experience with data management and manipulation techniques for AI applications.

Tech Skills (Preferred) :

- Experience with specific AI frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn)

- Familiarity with cloud-based AI services (e.g., AWS SageMaker, Azure Machine Learning)

- Knowledge of explainable AI (XAI) techniques and ethical considerations in AI development

- Experience with MLOps tools for deployment and management of AI models